How Today's Enterprises Keep Their Data Safe, Within Reach and Accurate
How Today's Enterprises Keep Their Data Safe, Within Reach and Accurate Pixabay

Businesses these days are generating more data than ever before. As the amount of data generated grows, the need to use these data becomes more urgent than ever. According to some estimates, more than 150 zettabytes, or 150 trillion gigabytes will need analysis by 2025.

Whether it’s financial, operational, or it powers an app of some kind, business data holds immense promise for organizations, but most companies are grappling with the challenges that are inherent to processing their data. A survey conducted by NewVantage Partners revealed that only 37% of firms considered themselves data-driven.

This shouldn't come as a surprise, given the hurdles that big data collection poses to security, storage, and operability. Let’s take a look at how three companies are helping organizations overcome these challenges and harness the power of their business data.

Decentralized Database Security With Bluzelle

Cybersecurity has become more important than ever, thanks to businesses migrating to the digital realm. Contrary to popular perception, data security is a vast field. Most organizations rely on application and network security but neglect the need to secure their data collection and storage.

A simple reason for this is that it's hard to conduct constant checks on data security when applications generate mountains of data simultaneously. As business operations grow, the resources required to perform such checks make the entire process unfeasible.

The only solution is to plan secure storage during the data architecture stage. This is where Bluzelle’s decentralized database comes in handy. Bluzelle's DB stores data across a series of nodes around the world. By doing this, companies can stop worrying about a single point of failure.

Scalability is also easy, since nodes distributed around the world make access to increased storage simple. Most importantly, data is secured through a consensus algorithm that ensures it can be updated only by the owner.

Bluzelle DB doesn't function like a traditional decentralized database. Those databases usually operate as blockchains that store data permanently. The result is increased storage costs and a clunky framework for applications. Instead, their solution stores data more like a traditional DB, by deleting and updating entries at a low cost, while utilizing the security benefits of the blockchain.

By integrating with a variety of programming languages such as javascript, Python, and Go, Bluzelle makes it easy for companies to build decentralized apps on their DB solution and brings the best of traditional and decentralized worlds to organizations.

A Familiar Front End for Reporting With DataRails

New-fangled technology can be appealing unto itself, but legacy solutions are often a company's best bet, given how deeply ingrained they can be in processes. A good example of this is Microsoft Excel. The spreadsheet might be a relic of the 90s, but as far as CFOs are concerned, it remains the go-to solution for financial calculations of any kind.

Despite generations of financial professionals knowing nothing but Excel, they're quick to recognize the limitations the app imposes on them. For starters, manual processes are almost compulsory when using Excel, since the app’s dynamic programming capabilities are highly limited.

As the amount of data collected grows, companies employing manual processes cannot hope to complete work cycles on time. However, they cannot abandon Excel either, as the cost of migrating bespoke business logic to a new system is prohibitive. The solution is to therefore integrate a modern solution within the familiar Excel front end.

This is precisely what DataRails offers. Backed by powerful reporting and data visualization dashboards, DataRails brings the power of deep analysis into Excel. Finance employees can run ad-hoc reports and drill deep into their data within Excel itself.

One of the biggest cost centers in manual data reconciliation processes lies in data collection and cleaning. Companies draw data from various sources, and these data have to be formatted and validated. Given the size of data being collected, completing this task with 100% accuracy manually is impossible.

DataRails automates the collection and consolidation process. Data from all sources are automatically formatted and pulled into a spreadsheet of your team's choice. With a single source of truth established, reporting teams can focus on analyzing financials and carrying out value-add processes instead of performing clerical tasks.

CFOs can trust their numbers better and implement new workflows with minimal disruption. DataRails's solution is flexible enough to be used standalone as well. Their dashboards provide interactive and visually appealing data representations that allow finance teams to slice and dice their reports in new ways.

Information Accuracy Validation With Constellation

Decentralization offers organizations the ability to scale quickly thanks to its flexibility. Organizations can quickly reorient themselves to serve their customers. A typical decentralized business model involves a series of microservices or apps communicating with one another, transmitting data, and leveraging it to create a platform that rests on top of these apps.

As the amount of data being collected increases exponentially, data validation becomes important. A decentralized network might be flexible, but it's hard to validate data sources. The solution to this problem has been data tokenization via smart contracts.

Building a product that leverages secured microservices that communicate with legacy and new apps, while maintaining scalability is a tough task. This is where Constellation’s Directed Acyclic Graph model, called Hypergraph, enters the picture.

By taking care of information validation and securing data that needs to be widely shared through a unique Proof of Reputable Observation (PRO) model, developers can easily send data across their ecosystem without worrying about violating data privacy or security protocols.

The PRO model is an evolution of existing consensus models that are inadequate for distributed infrastructure. By combining machine learning with existing models, Constellation has developed a secure communications protocol designed for scalability and app ecosystem growth.

The result is that the size of the ecosystem grows thanks to deeper insights generated from shared data. Organizations experience greater output, customer satisfaction driven by analytics, and bottom-line growth.

Challenging but Rewarding

Business data holds massive potential for businesses, and the challenges it brings are evolving. Thanks to these three innovative companies, organizations are overcoming the hurdles of data management and are increasing the value they provide to their customers.